Development of a Prediction Model for Splash and Spray

Abstract

Under some conditions splash and spray create a significant nuisance to road users and some evidence suggests that they contribute to a small but measurable proportion of accidents. This paper reports on the development of a prediction model for splash and spray. The work has been funded by the Federal Highway Administration in order to assist engineers in decisions concerning the type and priority of maintenance on the road network. Ultimately, this could deliver a range of benefits including increased user satisfaction with the network, reduced accidents and a reduction in the detrimental effect of pollutants being deposited on the road verges and street furniture. The approach taken has been, firstly, to develop a method for predicting the depth of water that builds up on the road surface, considering the rainfall rate, pavement geometry and surface type. Models obtained from the literature have been validated through measurements of water depth carried out in a flume, using a number of typical road surfaces. Secondly, computational fluid dynamics has been used to estimate the level of nuisance to road users of the various mechanisms of splash and spray generation.